Analyzing the Spatial Distribution of LST and Its Relationship With Underlying Surfaces in Different Months by Classification and Intersection

Abstract

Urban heat islands (UHIs) have become one of the most critical issues around the world, especially in the context of rapid urbanization and global climate change. Extensive research has been conducted across disciplines on the factors related to land surface temperature (LST) and how to mitigate the UHI effect. However, there remain deficiencies in the exploration of LST changes across time and their relationship with underlying surfaces in different temperature ranges. In order to fill the gap, this study compared the LST of each month by using the quantile classification method taking the Landsat 8 images of Nanjing on May 18th, July 21st, and October 9th in 2017 as the subject and then calculated the differences between July and May as well as that between July and October by an intersection tool taking the LST classes of July as the baseline. Additionally, the spatial pattern of each temperature class and intersection area was analyzed with the help of several landscape metrics, and the land contribution index (LCI) was utilized to better quantify the thermal contribution of each underlying surface to the area. The results indicated that the difference between months mainly reflected in the medium temperature area, especially between July and October, in which landscape patterns illustrated a trend of fragmentation and decentralization. The proportions of underlying surfaces in different types of intersection revealed the distinction of their warming and cooling degrees over time, in which the warming degree of other rigid pavement was higher in the warming process from May to July, and the cooling degree of buildings was greater in the cooling process from July to October. The LCI of each underlying surface in the entire study area was different from that in each temperature class, indicating that underlying surfaces had distinguished thermal contributions in different temperature ranges. This study is expected to fill the gap in previous studies and provide a new perspective on the mitigation of UHI.